Description Usage Arguments Running ABC Re-running ABC iterations Continuing ABC iterations Methods Author(s) References See Also
The approximate Bayesian computation (ABC) algorithm for estimating the parameters of a partially-observed Markov process.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ## S4 method for signature 'pomp'
abc(object, Nabc = 1, start, proposal,
pars, rw.sd, probes, scale, epsilon,
verbose = getOption("verbose"), ...)
## S4 method for signature 'probed.pomp'
abc(object, probes,
verbose = getOption("verbose"), ...)
## S4 method for signature 'abc'
abc(object, Nabc, start, proposal,
probes, scale, epsilon,
verbose = getOption("verbose"), ...)
## S4 method for signature 'abc'
continue(object, Nabc = 1, ...)
## S4 method for signature 'abc'
conv.rec(object, pars, ...)
## S4 method for signature 'abcList'
conv.rec(object, ...)
## S4 method for signature 'abc'
plot(x, y, pars, scatter = FALSE, ...)
## S4 method for signature 'abcList'
plot(x, y, ...)
|
object |
An object of class |
Nabc |
The number of ABC iterations to perform. |
start |
named numeric vector; the starting guess of the parameters. |
proposal |
optional function that draws from the proposal distribution. Currently, the proposal distribution must be symmetric for proper inference: it is the user's responsibility to ensure that it is. Several functions that construct appropriate proposal function are provided: see MCMC proposal functions for more information. |
rw.sd |
Deprecated. Will be removed in a future release.
Specifying |
probes |
List of probes (AKA summary statistics).
See |
scale |
named numeric vector of scales. |
epsilon |
ABC tolerance. |
verbose |
logical; if TRUE, print progress reports. |
pars |
Names of parameters. |
scatter |
optional logical;
If |
x |
|
y |
Ignored. |
... |
Additional arguments. These are currently ignored. |
abc
returns an object of class abc
.
One or more abc
objects can be joined to form an abcList
object.
To re-run a sequence of ABC iterations, one can use the abc
method on a abc
object.
By default, the same parameters used for the original ABC run are re-used (except for tol
, max.fail
, and verbose
, the defaults of which are shown above).
If one does specify additional arguments, these will override the defaults.
One can continue a series of ABC iterations from where one left off using the continue
method.
A call to abc
to perform Nabc=m
iterations followed by a call to continue
to perform Nabc=n
iterations will produce precisely the same effect as a single call to abc
to perform Nabc=m+n
iterations.
By default, all the algorithmic parameters are the same as used in the original call to abc
.
Additional arguments will override the defaults.
Methods that can be used to manipulate, display, or extract information from an abc
object:
conv.rec(object, pars)
returns the columns of the convergence-record matrix corresponding to the names in pars
.
By default, all rows are returned.
Concatenates abc
objects into an abcList
.
Diagnostic plots.
Edward L. Ionides ionides at umich dot edu, Aaron A. King kingaa at umich dot edu
T. Toni and M. P. H. Stumpf, Simulation-based model selection for dynamical systems in systems and population biology, Bioinformatics 26:104–110, 2010.
T. Toni, D. Welch, N. Strelkowa, A. Ipsen, and M. P. H. Stumpf, Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems Journal of the Royal Society, Interface 6:187–202, 2009.
pomp
, probe
, and the tutorials on the package website.
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